This is an extraordinary opportunity to join a new Alphabet company that will reimagine drug discovery through a computational- and AI-first approach.

We are assembling a world-class, multi-disciplinary team who want to drive forward groundbreaking innovations. As one of the first members of this pioneering organisation, you will play a meaningful role in building this team, embodying an inspiring, collaborative and entrepreneurial culture. 

This early-stage venture is on a mission to accelerate the speed, increase the efficacy and lower the cost of drug discovery. You’ll be working at the cutting edge of the new era of ‘digital biology’ and advancing a new type of biotech that will deliver transformative social impact for the benefit of millions of people. 

As a Director of Computational Biology you will build and lead a multi-faceted team of computational scientists to deliver new biological insights via the application of both AI and classical computational methods in the context of drug discovery. 

What you will do 

Work with a broad collaborator group to develop an ambitious research roadmap to interrogate a variety of biological phenomena relevant for drug discovery via a comprehensive set of cutting edge computational methods 
Establish a team of outstanding computational biology experts spanning a variety of sub-fields such as genomics, statistical genetics, imaging, proteomics, epidemiology, and systems biology.
Lead the team to execute on the research roadmap and deliver biological insights in support of the company’s drug discovery efforts.
Develop a comprehensive experimental and data strategy in support of overall research goals.
Effectively deploy a variety of published and proprietary machine learning models and statistical analysis methods to achieve research goals. 
Be a key member of the leadership team, harmoniously collaborating with other groups, such as Drug Design, Medical Research, ML Research, Data Engineering, and others in delivery of the overall company mission.
Enable, coach and mentor your team. 
 

Skills and qualifications 

Demonstrated expertise in genomics, and optionally, transcriptomics, statistical genetics, and other bioinformatics methods.
Hands-on experience in applying ML (especially deep learning) models in the field of computational biology.
Detailed understanding of a variety of genomic data analysis methods, from data generation and QC, to variant calling, to a broad array of downstream analyses including GWAS. 
Solid experience with experimental design and statistical analysis.
Experience with a variety of assaying techniques, including NGS, cell-based assays, functional genomics, single-cell techniques, and image-based assays with expertise in their respective data analysis approaches. 
Familiarity with genomic data processing pipelines and tools.
Expertise in applying computational biology methods to the process of drug discovery, such as methods used for disease modeling and target discovery, as well as biomarker development. 
Experience leading research teams and developing and driving research roadmaps.
Experienced in building inclusive teams and creating equitable interview/assessment processes
Ability to effectively communicate scientific concepts to a variety of audiences.
PhD, or equivalent experience in Genomics, Molecular Biology, Genetics, Systems Biology, Computer Science, Statistics, Machine Learning, or a related field.
Behaviours and attributes
Grounded and original problem solver: Combines the best from industry with new ideas and creative approaches, taking well-informed risks to advance progress
Motivated by purpose and impact: Self-directed, chooses the most effective path to maximise impact in pursuit of higher level purpose, operates at pace with a clear bias for action
Experimental: Comfortable with ambiguity, embraces new ideas, responds quickly and adapts to maximise opportunities
Collaborative and inclusive: Willing to go above and beyond, and builds strong partnerships with a variety of collaborators
Curious mentality: Strong interest in self-development, learns from setbacks as well as successes
Hybrid working: It’s hugely important for us to be able to share knowledge and establish relationships with each other, and we find it easier to do this if we spend time together in person. This is why we’ve decided to follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tue, Wed, and one other day depending on which team you’re in).  As an equal opportunities employer we are committed to building an equal and inclusive team. If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.

Isomorphic Labs welcomes applications from all sections of society. We are committed to equal employment opportunity regardless of age; disability; gender reassignment; marriage and civil partnership; pregnancy and parental; race; religion or belief; sex; sexual orientation or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

It would be helpful if you could answer the following questions. Your application won’t be effected by the answers you provide, the information is helping us to understand the profile of individuals interested in joining IsoLabs.

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